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Learn MoreAs Seen in Inside Precision Medicine
Researchers at the Technion – Israel Institute of Technology have developed an artificial intelligence (AI) model designed to help guide whether to administer chemotherapy directly after tumor resection in breast cancer patients. The model, which uses high-resolution images from hematoxylin and eosin (H&E)-stained tumor samples collected at the time of diagnosis, predicts both the risk of cancer recurrence and the likelihood that a patient will benefit from chemotherapy. The research, published in The Lancet Oncology, identifies patterns and signals in the tumor that might otherwise escape detection.
“These are complex biological signals that the human eye cannot consistently quantify,” said first author Gil Shamai, PhD, a postdoctoral researcher at Technion. “The model integrates many subtle cues to generate a score that reflects both recurrence risk and expected benefit from chemotherapy.”
To create the tool, the researchers used deep learning methods to evaluate tumor regions and the surrounding tumor microenvironment to identify patterns linked to cancer behavior such as cell division, immune response, and tissue structure. This approach allows the model to estimate the Oncotype DX 21-gene recurrence score without requiring genomic testing.